1. Field of the Invention
This invention relates generally to a system and method for providing lane changing maneuvers for an autonomously driven vehicle and, more particularly, to a system and method for providing lane changing maneuvers for an autonomously driven vehicle that includes using adjacent lane position information provided by a vehicle navigation controller to steer the vehicle to the adjacent lane.
2. Discussion of the Related Art
The operation of modern vehicles is becoming more autonomous, i.e., vehicles are able to provide driving control with less driver intervention. Cruise control systems have been on vehicles for a number of years where the vehicle operator can set a particular speed of the vehicle, and the vehicle will maintain that speed without the driver operating the throttle. Adaptive cruise control systems have been recently developed in the art where not only does the system maintain the set speed, but also will automatically slow the vehicle down in the event that a slower moving vehicle is detected in front of the subject vehicle using various sensors, such as radar, lidar and cameras. Modern vehicle control systems may also include autonomous parking where the vehicle will automatically provide the steering control for parking the vehicle, and where the control system will intervene if the driver makes harsh steering changes that may affect vehicle stability and lane centering capabilities, where the vehicle system attempts to maintain the vehicle near the center of the lane. Fully autonomous vehicles have been demonstrated that drive in simulated urban traffic up to 30 mph, while observing all of the rules of the road.
As vehicle systems improve, they will become more autonomous with the goal being a completely autonomously driven vehicle. Future vehicles will likely employ autonomous systems for lane changing, passing, turns away from traffic, turns into traffic, etc. Examples of semi-autonomous vehicle control systems include U.S. patent application Ser. No. 12/399,317 (herein referred to as '317), filed Mar. 6, 2009, titled “Model Based Predictive Control for Automated Lane centering/changing control systems,” assigned to the assignee of this application and herein incorporated by reference, which discloses a system and method for providing steering angle control for lane centering and lane changing purposes in an autonomous or semi-autonomous vehicle. U.S. patent application Ser. No. 12/336,819, filed Dec. 17, 2008, titled “Detection of Driver Intervention During a Torque Overlay Operation in an Electric Power Steering System,” assigned to the assignee of this application and herein incorporated by reference, discloses a system and method for controlling vehicle steering by detecting a driver intervention in a torque overly operation.
There are basically two different scenarios where an autonomously driven vehicle may want to change from one travel lane to an adjacent travel lane. The vehicle navigation controller on board the vehicle may change the vehicle route because the driver initiates a route change or some other factor, such as traffic congestion, causes the navigation controller to change route. Also, the autonomously driven vehicle may need to change lanes because an obstructing object, such as a slow moving vehicle, is in front of the vehicle. When the vehicle controller on board the vehicle detects an object via sensors in the pathway of the vehicle and wants to change lanes, the vehicle controller will send a request to the navigation controller for the navigation controller to provide a route segment for the vehicle to go around the object.
Executing autonomous lane changing maneuvers for every possible driving scenario, such as vehicle rerouting, overtaking and object avoidance, under different traffic situations is technologically challenging. The use of advanced knowledge about the road geometry, vehicle kinematics and location to determine safe and smooth lane changing behavior and trajectory generation for every individual driving scenario is cumbersome and computationally expensive. For example, known systems require the vehicle controller to generate a large number of plausible candidate vehicle trajectories at every vehicle position node as the vehicle travels to identify a clear space to execute lane changes. Currently, the vehicle controller calculates several and many nodes along a vehicle route, where each node represents a position and a speed of the vehicle, and where the vehicle controller steers the vehicle from one node to another node along the calculated route called a vehicle trajectory. As the vehicle moves from one position to another, the vehicle controller calculates a large number of such candidate vehicle trajectories that the vehicle can possibly travel along between the nodes, where only one of those trajectories would be selected as the best route segment by the vehicle controller, based on an optimized cost function, for the vehicle to travel along when performing the lane changing maneuver. Because of the high computation requirements associated with creating a large number of trajectories every time the vehicle moves from one position to another (e.g., at 100 millisecond position updates), the latency, i.e., the time it takes to determine the best route segment to travel on, is relatively long. Further, known solutions for lane changing may not work across multiple vehicle platforms and different road topologies.